Shenghui Wang is an Assistant Professor in Human Media Interaction with a focus on hybrid human-AI systems. Affiliated with OCLC Research Europe since 2012, his work bridges artificial intelligence, virtual reality, and cultural heritage digitization. Research Interests: Ontology modeling, eye-tracking integration, multimodal conversational agents, and FAIR metadata principles for cultural data Key Activities: Organized HHAI 2025 and ISWC 2025 conferences; presented at ICT Open 2024 and Hybrid Intelligence Consortium meetings Current Work: Developing social VR frameworks for collaborative art exploration and evaluating RAG-based chatbots in healthcare contexts His recent publications emphasize Human-Computer Interaction in educational and cultural settings, with specific attention to: Personalized learning systems Virtual heritage applications Ontology-driven VR environments Author disambiguation algorithms Wang's research contributes to UN Sustainable Development Goals through innovative applications in education, cultural preservation, and accessible AI systems.
Koray Karaca is an Assistant Professor in Philosophy , specializing in the intersection of Artificial Intelligence , Machine Learning , and Philosophy of Science . His work critically examines epistemic and ethical dimensions of AI, with a focus on Knowledge Representation and Reasoning , Human-AI Interaction , and Experimental Methodology in high-energy physics. Research interests span Artificial Intelligence , Autonomous Agent Systems , and Scientific Modeling . His studies analyze diagrammatic representations in collaborative particle physics experiments, inductive risk in ML modeling, and robustness in experimental results. Recent publications explore experimental robustness , Higgs mechanism epistemology , and ethical frameworks for AI . His work combines Physics , Machine Learning , and Philosophical Analysis , addressing challenges in theory-ladenness , data acquisition , and interdisciplinary collaboration . Karaca’s contributions include developing design thinking frameworks for AI systems and evaluating scientific unification across physics domains. His studies on binary classification models highlight the societal implications of technical decisions in machine learning.
Dr. Margarita Leib is an Assistant Professor in the Department of Social Psychology at Tilburg University's School of Social and Behavioral Sciences. Her research sits at the intersection of psychology and economics, focusing on decision-making processes in ethical dilemmas and human-AI interactions. Research interests include: Behavioral ethics and dishonesty in social contexts Impacts of AI algorithms on moral decision-making Willful ignorance and information avoidance strategies Prosocial/antisocial behavior in organizational settings Cross-cultural differences in ethical behavior Recent publications (2023-2025) cluster around three themes: AI's influence on ethical decisions (computational ethics), psychological mechanisms of dishonesty (behavioral ethics), and meta-analyses of information avoidance strategies (cognitive psychology). Her work appears in high-impact journals including Computers in Human Behavior and Psychological Bulletin. She is currently involved in the multinational research project 'The obligation to obey the law: exploring National Differences' and leads a Digital Sciences for Society-funded project examining interventions in unethical AI-driven decisions.
Marloes Hagens is a PhD candidate at the Rotterdam School of Management (RSM) , affiliated with the Department of Finance at Erasmus University Rotterdam. Her research explores intersections of finance, behavioral economics, and algorithmic ethics. Research Interests: Behavioral Economics: Focused on how AI-generated advice impacts human honesty and ethical decision-making. Algorithmic Ethics: Investigating the role of artificial intelligence in shaping financial behavior. Human-AI Interaction: Analyzing the influence of algorithmic transparency on trust and compliance. Publications: Her recent work examines the ethical implications of AI in economic contexts, particularly dishonesty dynamics.
Prof. Dr. Ir. Herman van der Kooij is a leading academic in Biomechatronics and Rehabilitation Technology , affiliated with the University of Twente (0.8 FTE) and Delft University of Technology (0.2 FTE). He chairs the Biomechatronics group at UT and has made groundbreaking contributions to wearable robotics for medical and industrial applications. His research focuses on human balance control , neuromechanical modeling , and exoskeleton-assisted mobility . He develops technologies like the LOPES gait rehabilitation robot and the Mindwalker exoskeleton , combining experimental and computational approaches to advance wearable robotics. His work spans soft robotics , real-time EMG-driven control , and low-cost sensor integration . Van der Kooij has published over 170 peer-reviewed works and received prestigious Dutch VIDI and VICI grants . He leads national programs in Wearable Robotics and 4TU Soft Robotics , and serves as associate editor for IEEE journals. He founded two specialized labs: the Rehabilitation Robotics Laboratory (with Roessingh Research and Development) and the Virtual Reality Human Performance Lab , which integrates robotics, motion capture, and VR for testing. He emphasizes active learning in courses like Biorobotics and Biomechatronics , encouraging students to learn through hands-on projects and mistakes. His work also explores non-medical applications of exoskeletons, including industrial ergonomics and entertainment technology .
Antonios Liapis is an Associate Professor at the Institute of Digital Games, University of Malta. He completed his PhD in September 2014 under the supervision of Georgios N. Yannakakis at the IT University of Copenhagen. His academic journey includes an M.Sc. in Information Technology from the same institution and a 5-year Diploma in Electrical and Computer Engineering from the National Technical University of Athens. Dr. Liapis has held various academic positions at the University of Malta: Post-doctoral Researcher (2014-2015), Lecturer (2015-2020), Senior Lecturer (2020-2022), and currently Associate Professor (2022-present). He has served as General Chair for multiple international conferences including FDG (2020), GALA (2019), and EvoMusArt (2018-2019). He is an Associate Editor of the IEEE Transactions on Games and a member of the Games Technical Committee of the IEEE Computational Intelligence Society. His research focuses on Artificial Intelligence as an autonomous creator and as a facilitator of human creativity. Key areas include computationally intelligent tools for game design and computational creators that blend semantics, visuals, sound, plot, and level structure to create various game genres including horror, adventure, shooter, and dungeon crawler games. His work has resulted in over 150 peer-reviewed publications and several research awards. Dr. Liapis has secured multiple research grants from the European Commission, including projects on AI-powered robotic material recovery, virtual reality aided design, and learning science through coding and play. His notable project series "Data Adventures" demonstrates the use of open data from Wikipedia, DBpedia, Wikimedia Commons, and OpenStreetMap to automatically generate adventure games with complete plots, characters, items, and locations. His scientific contributions have been recognized with several awards including Best Paper Awards at major conferences, Best Reviewer Award, and Runner-Up Best Student Paper Award. Dr. Liapis has also co-organized 16 workshops in diverse conferences throughout his career. Research interests include: Artificial Intelligence for creative applications Procedural Content Generation in games Computational Creativity systems Machine Learning for game design Affective Computing in virtual environments Human-AI collaboration in creative processes His recent work shows a strong trend toward integrating Large Language Models with game design, exploring quality diversity algorithms for creative applications, and advancing affect modeling for improved player experience. The research spans computer science, artificial intelligence, game studies, and human-computer interaction, with practical applications in education, entertainment, and design.
Dr. Florian Pethig is an Assistant Professor in the Department of Information Systems and Operations Management at Tilburg School of Economics and Management (TiSEM), Tilburg University. He also serves as an External Lecturer at Mannheim Business School for multiple courses during 2024-2025. His research focuses on digital platforms, online communities, and the societal impact of information technology. Key areas include: Algorithmic bias and gender discrimination in evaluation processes Socialization dynamics and newcomer retention in online communities Digital government services and inclusion for people with disabilities Moderation policies in online brand communities Dr. Pethig's research examines how technology impacts user behavior and welfare, particularly for marginalized groups. His work combines empirical methods with theoretical frameworks from information systems, social psychology, and public administration to address real-world challenges in digital platforms and government services. His research has been published in top journals including MIS Quarterly, Journal of Business Ethics, Government Information Quarterly, and Journal of the Association for Information Systems. His work on algorithmic bias has received media coverage in Psychology Today and Forbes France. Dr. Pethig has received research funding from multiple prestigious sources: Dutch Research Council (NWO) German Academic Exchange Service (DAAD) Joachim Herz Foundation Wikimedia Deutschland He is also a Co-Investigator on the VIA PRUDENTI project focused on developing responsible and efficient infrastructure delivery networks. Dr. Pethig teaches 'Enterprise Architecture as a Business Strategy' and 'Information Management for Pre-Master' at Tilburg University, where his courses have received excellent evaluations (4.7 and 4.3 out of 5). He previously taught various information systems courses at the University of Mannheim and serves as an External Lecturer at Mannheim Business School. In 2023, Dr. Pethig was awarded the Best Associate Editor Award at ECIS (European Conference on Information Systems). He regularly serves as a reviewer for leading journals including Management Science, MIS Quarterly, and Information Systems Research.
Dr. Jan Mathijs Schoffelen serves as Associate Principal Investigator at Radboud University's Donders Institute for Brain, Cognition and Behaviour, where he leads research on brain connectivity using MEG and EEG methodologies. He represents the Norris PI group in the DCCN Representative Council and is a core developer of the globally adopted FieldTrip open-source analysis toolbox, contributing to major initiatives including the Human Connectome Project and MOUS. His research centers on neural synchronization mechanisms during cognitive processes, particularly investigating how brain rhythms facilitate inter-regional communication in language tasks. He addresses critical challenges in non-invasive electrophysiology including signal-to-noise optimization and source reconstruction validity, advancing methods to interpret neural interactions in healthy human cognition where invasive techniques are impossible. Publications reveal consistent focus on gamma-band coherence in sensorimotor systems, attentional modulation through synchronization, and computational frameworks for connectivity analysis. His work bridges theoretical neuroscience with practical tool development, demonstrating growing emphasis on language processing applications alongside foundational motor and visual system investigations. Scientific recognition includes: Young investigator award at Biomag conference, Sapporo (2008) NWO VIDI-grant for independent research leadership (2015) As Principal Investigator, he directs the FieldTrip project while contributing to large-scale collaborations like the Human Connectome Project. His NWO VIDI grant supports methodological innovations for non-invasive connectivity analysis, enabling new investigations into cognitive neuroscience. Embedded within the Donders Institute's Norris research group, he collaborates through the international FieldTrip community to advance electrophysiological analysis standards, maintaining active development of open-source tools that serve thousands of neuroscientists worldwide.
Marco Dorigo serves as Research Director for the Belgian F.R.S.-FNRS and co-director of IRIDIA, the artificial intelligence laboratory at the Free University of Brussels. He holds the position of Editor-in-Chief for Springer's Swarm Intelligence journal, establishing him as a leading authority in bio-inspired computing and collective intelligence systems. His research fundamentally centers on swarm intelligence and its intersections with robotics, multi-agent systems, and adaptive computing. Dorigo pioneered ant colony optimization algorithms and continues to drive innovation in human-swarm interaction, reality gap mitigation, and self-organizing systems. His work bridges theoretical computer science with practical applications in robotics and complex system design, emphasizing emergent behaviors and decentralized control mechanisms. Dr. Dorigo's scientific accolades include the Italian Prize for Artificial Intelligence (1996), Marie Curie Excellence Award (2003), Dr. A. De Leeuw-Damry-Bourlart award (2005), Cajastur International Prize for Soft Computing (2007), ERC Advanced Grant (2010), and the IEEE Frank Rosenblatt Award (2015). He maintains elite recognition as a Fellow of IEEE, AAAI, and ECCAI. As co-director of IRIDIA, he leads a multidisciplinary research collective advancing swarm robotics and collective intelligence through experimental validation and theoretical frameworks. His leadership in the ERC Advanced Grant project demonstrates sustained capacity to secure major research funding while mentoring the next generation of researchers in computational intelligence.
Pengcheng Liu is an Associate Professor in the Department of Computer Science at the University of York, holding this position since January 2020. He maintains active memberships in IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS), and the International Federation of Automatic Control (IFAC), while serving on the IEEE Technical Committee for Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. His research spans robotics, machine learning, automatic control, and optimization, with specialization in humanoid robotics, rehabilitation systems, agricultural applications, and human-computer interaction. Key focus areas include developing lightweight neural networks for embedded agricultural systems, bionic-companionship frameworks for service robots, EMG-controlled rehabilitation devices, and precise control of robotic manipulators using ROS/Gazebo. His work consistently bridges theoretical control systems with practical implementations in healthcare and precision agriculture. Analysis of his publication trends reveals strong emphasis on applying machine learning to real-world robotics challenges, particularly in resource-constrained environments (e.g., agricultural robotics with efficient neural networks) and human-centered applications (e.g., rehabilitation gloves and brain-computer interfaces). Recent work demonstrates increasing integration of computer vision with control systems for autonomous operation. His notable scientific awards include: Global Peer Review Awards from Web of Science (2019) Outstanding Contribution Awards from Elsevier (2017) Dr. Liu has secured and managed research funding through major programs including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, and NSFC. He serves as a regular reviewer for EPSRC, NIHR, and NSFC grant panels while reviewing for over 30 flagship journals and conferences in robotics, AI, and control systems. His editorial roles include Associate Editor for IEEE Access and PeerJ Computer Science, where he has edited 17 publications. Though specific lab affiliations aren't detailed, his research in agricultural robotics, rehabilitation systems, and humanoid platforms suggests active collaboration with York's robotics and AI research groups, particularly in developing practical implementations of control algorithms and machine learning models for real-world deployment.
Paulo Jorge Coelho serves as an Adjunct Professor in the Electrical Engineering Department at the School of Technology and Management, Polytechnic University of Leiria, and as an integrated researcher with the ROBiTECH (Advanced Robotics and Smart Factories) group at INESC Coimbra's Leiria delegation. With over 20 years of academic experience since 2004, he specializes in Microprocessors, Industrial Automation, and Computer Vision instruction. Education: Ph.D. in Informatics (2019), Trás-Os-Montes and Alto Douro University Specialization in Automation and Control (2007), Coimbra University Bachelor of Electrical Engineering (2004), Coimbra University Research Focus: His work bridges industrial automation and computer vision with cutting-edge machine learning applications in biomedical imaging, ambient assisted living, and assistive technologies. Current projects emphasize practical implementations for reducing physical impairments and enhancing healthcare solutions through deep learning frameworks. Publication Trends: Recent work (2024-2025) reveals strong interdisciplinary convergence between healthcare diagnostics (schizophrenia/EEG analysis, perinatal depression prediction) and industrial/computer vision systems (sports analytics, activity recognition). His research consistently leverages sensor fusion and deep learning architectures to solve real-world problems across medical and engineering domains. Professional Engagement: Active member of the Portuguese Engineers Order and Portuguese Association for Pattern Recognition, with significant editorial contributions (89+ edited articles) across AI and computer vision domains. Previously served as course director and Scientific-Pedagogical Committee member for the Master's in Electrical and Electronic Engineering. Research Infrastructure: Operates within ROBiTECH's advanced robotics ecosystem at INESC Coimbra, focusing on smart factory solutions and human-robot interaction systems. His lab environment integrates industrial automation testbeds with biomedical sensor networks for cross-domain innovation.
Dr. Michael Veale serves as a Lecturer in Digital Rights and Regulation at the Faculty of Laws, University College London, where his work critically examines power dynamics in digital technology governance through interdisciplinary lenses of law, computer science, and human-computer interaction. His research portfolio emphasizes: Digital Rights and Regulation frameworks Policy implications of emerging technologies Societal impacts of algorithmic systems Legal dimensions of data governance Human-centered technology design principles Veale has co-authored landmark reports for the Royal Society, British Academy, Law Society of England and Wales, and Commonwealth Secretariat, with findings directly influencing parliamentary debates and international policy documents worldwide, demonstrating significant real-world impact beyond academic publication.
